Sentence Similarity
sentence-transformers
Safetensors
English
xlm-roberta
feature-extraction
Generated from Trainer
dataset_size:43344766
loss:MultipleNegativesRankingLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use deadf00d/multilingual-e5-mnrl-outcomes with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use deadf00d/multilingual-e5-mnrl-outcomes with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("deadf00d/multilingual-e5-mnrl-outcomes") sentences = [ "West Georgia @ Samford Total Points Scored Under 157.5", "Middle Tennessee @ UAB 1st Half Alternate Total Points 4 Under 69.5", "West Georgia @ Samford O/U Live Betting Under 157.5", "TCU at Santa Clara (Neutral Venue) Spread Santa Clara -1.5" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
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